Exact simulation of integrate-and-fire models with synaptic conductances
Exact simulation of integrate-and-fire models with synaptic conductances
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DOI：
10.1162/neco.2006.18.8.2004
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发表时间：
2006-08-01
影响因子：
2.9
通讯作者：
Brette, R
中科院分区：
文献类型：
--
作者：
Brette, R
计算神经科学在很大程度上依赖于大型神经元模型网络的模拟。基本上有两种模拟策略：（1）使用近似方法（例如，龙格库塔）与尖峰时间分箱的时间步骤和（2）计算尖峰时间准确地在事件驱动的方式。在大型网络中，任何一种策略的最佳算法的计算时间都与突触的数量呈线性关系，但每种策略都有自己的优点和限制：近似方法可以应用于任何模型，但不精确;精确模拟可以避免数值伪影，但仅限于简单模型。以前的工作集中在提高近似方法的精度。在这篇文章中，我们将可以精确模拟的模型范围扩展到一个更现实的模型：具有指数突触电导的积分和激发模型。
Computational neuroscience relies heavily on the simulation of large networks of neuron models. There are essentially two simulation strategies: (1) using an approximation method (e.g., Runge-Kutta) with spike times binned to the time step and (2) calculating spike times exactly in an event-driven fashion. In large networks, the computation time of the best algorithm for either strategy scales linearly with the number of synapses, but each strategy has its own assets and constraints: approximation methods can be applied to any model but are inexact; exact simulation avoids numerical artifacts but is limited to simple models. Previous work has focused on improving the accuracy of approximation methods. In this article, we extend the range of models that can be simulated exactly to a more realistic model: an integrate-and-fire model with exponential synaptic conductances.